How to Use the HubSpot Sales Hub MCP in Pydantic AI

Q: How do I configure Pydantic AI to see HubSpot Sales Hub tools?

Initialize the MCPToolset with your server URL and add it to your agent's toolset list. The models are then automatically generated.

Type-safe HubSpot Sales Hub operations for your Pydantic AI agent workflows.

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Connect HubSpot Sales Hub MCP to Pydantic AI

Create your Vinkius account to connect HubSpot Sales Hub to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HubSpot Sales Hub with Pydantic AI

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Claude

Perplexity

Strictly typed deal operations

Every response from `hs_create_deal` is validated against your Pydantic models at runtime. This prevents silent failures in your Pydantic AI agent logic. If the CRM returns unexpected data, the process halts immediately. You get clean, predictable data structures every single time.

Reliable pipeline monitoring

Use `hs_deals_by_stage` to pull structured deal lists into your agent's context. Pydantic AI ensures the returned schema matches your internal expectations. This makes your sales analysis code far more stable. You catch data inconsistencies before they affect your reporting.

Integrated quote management

Retrieve quote status with `hs_list_quotes` and let your agent act on the results. The type-safe interface ensures your Pydantic AI agent handles approval states correctly. It turns your CRM into a verifiable data source for your agent. You stop worrying about field types and start shipping features.

Setup guide

Set up HubSpot Sales Hub MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "hubspot-sales-hub-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to HubSpot Sales Hub tools.",
)

result = await agent.run("List recent HubSpot Sales Hub transactions")
print(result.output)

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Common questions about HubSpot Sales Hub MCP in Pydantic AI

It enforces strict data validation on every tool response. You get immediate errors if the CRM returns data that breaks your agent's model.

Initialize the `MCPToolset` with your server URL and add it to your agent's toolset list. The models are then automatically generated.

Yes. Since every tool call is modeled, the agent verifies the deal update arguments before the server even receives the request.

The server handles the secure transport, while Pydantic AI acts as the type-safe client. Your tokens remain local to your runtime.

The system treats your meeting outcomes as read-only objects. No data is cached by the agent framework, ensuring total privacy.

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